Architecture

In Lambda architecture there are 3 layers:

1. Batch layer This is the historical archive used to hold all of the data ever collected. This is usually a “data lake” system, such as Hadoop, though it could also be an online analytical processing (OLAP) data warehouse like Vertica or Netezza. The batch layer supports batch queries, which compute historical predefined and ad hoc analytics.

2. Speed layer The speed layer supports computing real-time analytics on fast-moving data as it enters the system. This layer is a combination of queuing, streaming, and operational data stores.

3. Serving layer This layer caches results from batch-layer computations so they are immediately available to answer queries. Computing batch layer queries can take time. Periodically, these analytics are re-computed and the cached results are refreshed in the serving layer.